Unraveling volatile metabolites in pigmented onion (Allium cepa L.) bulbs through HS-SPME/GC–MS-based metabolomics and machine learning
The findings suggest that the combination of HS-SPME/GC-MS and machine learning, particularly the random forest algorithm, is a powerful approach for characterizing and classifying volatile metabolite profiles in colored onions. This method holds potential for quality assessment and breeding applications.
Authors
- Jin-Chang Xiao
- Wengang Jin (ORCID: https://orcid.org/0000-0002-9838-3905)
- Jingyuan He
- Rongguang Yang
- Jinjin Pei (ORCID: https://orcid.org/0000-0003-1301-3620)
- A.M. Abd El‐Aty (ORCID: https://orcid.org/0000-0001-6596-7907)
- Kaiqi Cheng
Institutions
- Cairo University (EG)
- Shaanxi University of Technology (CN)
- Atatürk University (TR)
Publication Details
- Journal
- Frontiers in Nutrition
- Published
- 2025-04-22
- DOI
- https://doi.org/10.3389/fnut.2025.1582576
- Citations
- 4
- Primary Topic
- Garlic and Onion Studies
- Type
- article
- Field-Weighted Citation Impact
- 7.00